The incidence of cancer, in particular breast cancer and cervical cancer, is still high according to the statistical data in the United States. Early detection of the cancer is extremely important for successful treatment. However, it is not easy for the radiologists to quickly and accurately diagnose the pathological changes by using the original medical images such as, for example, mammograms and Pap smears, in which the abnormal changes are buried in surrounding tissue. Therefore, it is important to explore techniques to enhance desired components and filter out undesired components present in the medical images so that the radiologist and/or pathologist and other medical personnel can easily make a diagnosis and prescribe appropriate treatment.
Medical image processing with digital techniques is being increasingly used for such applications. It has been demonstrated that medical image processing is very helpful for the diagnosis. However, digital image processing is a manipulating-in-series method and is aided by computers and expensive electronic equipment. Often related software is complicated and time consuming for medical personnel to manipulate. Moreover, the digital methods also require many accessories for image sampling, transformations, processing, and output displays and results.
There still remains a need for simple and cost-effective systems that assist in medical image processing.